Overview

Dataset statistics

Number of variables22
Number of observations5922
Missing cells8825
Missing cells (%)6.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1023.6 KiB
Average record size in memory177.0 B

Variable types

Categorical10
Text9
Numeric1
DateTime1
Boolean1

Alerts

Avg Response Time is highly imbalanced (53.9%)Imbalance
Rating has 104 (1.8%) missing valuesMissing
Rating Count has 104 (1.8%) missing valuesMissing
Member Since has 1571 (26.5%) missing valuesMissing
Avg Response Time has 1685 (28.5%) missing valuesMissing
Last Delivery has 1574 (26.6%) missing valuesMissing
Order in Queue has 3761 (63.5%) missing valuesMissing

Reproduction

Analysis started2024-05-26 11:22:27.831360
Analysis finished2024-05-26 11:22:29.539310
Duration1.71 second
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

Category
Categorical

Distinct10
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
Music & Audio
734 
Programming & Tech
722 
Business
719 
Data
641 
Lifestyle
631 
Other values (5)
2475 

Length

Max length21
Median length17
Mean length13.288416
Min length4

Characters and Unicode

Total characters78694
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowData
2nd rowData
3rd rowData
4th rowData
5th rowData

Common Values

ValueCountFrequency (%)
Music & Audio 734
12.4%
Programming & Tech 722
12.2%
Business 719
12.1%
Data 641
10.8%
Lifestyle 631
10.7%
Writing & Translation 551
9.3%
Graphics & Design 545
9.2%
Video & Animation 514
8.7%
Digital Marketing 512
8.6%
Photography 353
6.0%

Length

2024-05-26T14:52:29.657307image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-26T14:52:29.823567image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
ValueCountFrequency (%)
3066
24.4%
music 734
 
5.8%
audio 734
 
5.8%
programming 722
 
5.7%
tech 722
 
5.7%
business 719
 
5.7%
data 641
 
5.1%
lifestyle 631
 
5.0%
translation 551
 
4.4%
writing 551
 
4.4%
Other values (7) 3495
27.8%

Most occurring characters

ValueCountFrequency (%)
i 9361
 
11.9%
6644
 
8.4%
a 5542
 
7.0%
n 5179
 
6.6%
s 5163
 
6.6%
e 4274
 
5.4%
t 4265
 
5.4%
r 3956
 
5.0%
g 3917
 
5.0%
o 3741
 
4.8%
Other values (21) 26652
33.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 78694
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 9361
 
11.9%
6644
 
8.4%
a 5542
 
7.0%
n 5179
 
6.6%
s 5163
 
6.6%
e 4274
 
5.4%
t 4265
 
5.4%
r 3956
 
5.0%
g 3917
 
5.0%
o 3741
 
4.8%
Other values (21) 26652
33.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 78694
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 9361
 
11.9%
6644
 
8.4%
a 5542
 
7.0%
n 5179
 
6.6%
s 5163
 
6.6%
e 4274
 
5.4%
t 4265
 
5.4%
r 3956
 
5.0%
g 3917
 
5.0%
o 3741
 
4.8%
Other values (21) 26652
33.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 78694
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 9361
 
11.9%
6644
 
8.4%
a 5542
 
7.0%
n 5179
 
6.6%
s 5163
 
6.6%
e 4274
 
5.4%
t 4265
 
5.4%
r 3956
 
5.0%
g 3917
 
5.0%
o 3741
 
4.8%
Other values (21) 26652
33.9%

Field
Categorical

Distinct35
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
video-editing
 
190
articles-blogposts
 
189
mixing-mastering
 
188
social-media-design
 
186
game-development
 
185
Other values (30)
4984 

Length

Max length29
Median length20
Mean length15.881966
Min length5

Characters and Unicode

Total characters94053
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowdata-engineering
2nd rowdata-engineering
3rd rowdata-engineering
4th rowdata-engineering
5th rowdata-engineering

Common Values

ValueCountFrequency (%)
video-editing 190
 
3.2%
articles-blogposts 189
 
3.2%
mixing-mastering 188
 
3.2%
social-media-design 186
 
3.1%
game-development 185
 
3.1%
producers 185
 
3.1%
financial-consulting-services 185
 
3.1%
software-development 185
 
3.1%
game-art 184
 
3.1%
business-plans 184
 
3.1%
Other values (25) 4061
68.6%

Length

2024-05-26T14:52:30.044322image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
video-editing 190
 
3.2%
articles-blogposts 189
 
3.2%
mixing-mastering 188
 
3.2%
social-media-design 186
 
3.1%
game-development 185
 
3.1%
producers 185
 
3.1%
financial-consulting-services 185
 
3.1%
software-development 185
 
3.1%
business-plans 184
 
3.1%
game-art 184
 
3.1%
Other values (25) 4061
68.6%

Most occurring characters

ValueCountFrequency (%)
e 11199
11.9%
s 8804
 
9.4%
i 8530
 
9.1%
a 7211
 
7.7%
n 7138
 
7.6%
t 6486
 
6.9%
- 6181
 
6.6%
o 5615
 
6.0%
r 4616
 
4.9%
g 4050
 
4.3%
Other values (15) 24223
25.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 94053
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 11199
11.9%
s 8804
 
9.4%
i 8530
 
9.1%
a 7211
 
7.7%
n 7138
 
7.6%
t 6486
 
6.9%
- 6181
 
6.6%
o 5615
 
6.0%
r 4616
 
4.9%
g 4050
 
4.3%
Other values (15) 24223
25.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 94053
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 11199
11.9%
s 8804
 
9.4%
i 8530
 
9.1%
a 7211
 
7.7%
n 7138
 
7.6%
t 6486
 
6.9%
- 6181
 
6.6%
o 5615
 
6.0%
r 4616
 
4.9%
g 4050
 
4.3%
Other values (15) 24223
25.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 94053
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 11199
11.9%
s 8804
 
9.4%
i 8530
 
9.1%
a 7211
 
7.7%
n 7138
 
7.6%
t 6486
 
6.9%
- 6181
 
6.6%
o 5615
 
6.0%
r 4616
 
4.9%
g 4050
 
4.3%
Other values (15) 24223
25.8%

Seller Level
Categorical

Distinct4
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
new seller
1658 
level 1
1538 
level 2
1468 
top rated seller
1258 

Length

Max length16
Median length7
Mean length9.751773
Min length7

Characters and Unicode

Total characters57750
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowlevel 1
2nd rowlevel 1
3rd rowlevel 1
4th rowlevel 1
5th rowlevel 1

Common Values

ValueCountFrequency (%)
new seller 1658
28.0%
level 1 1538
26.0%
level 2 1468
24.8%
top rated seller 1258
21.2%

Length

2024-05-26T14:52:30.188318image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-26T14:52:30.313317image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
ValueCountFrequency (%)
level 3006
22.9%
seller 2916
22.3%
new 1658
12.7%
1 1538
11.7%
2 1468
11.2%
top 1258
9.6%
rated 1258
9.6%

Most occurring characters

ValueCountFrequency (%)
e 14760
25.6%
l 11844
20.5%
7180
12.4%
r 4174
 
7.2%
v 3006
 
5.2%
s 2916
 
5.0%
t 2516
 
4.4%
n 1658
 
2.9%
w 1658
 
2.9%
1 1538
 
2.7%
Other values (5) 6500
11.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 57750
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 14760
25.6%
l 11844
20.5%
7180
12.4%
r 4174
 
7.2%
v 3006
 
5.2%
s 2916
 
5.0%
t 2516
 
4.4%
n 1658
 
2.9%
w 1658
 
2.9%
1 1538
 
2.7%
Other values (5) 6500
11.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 57750
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 14760
25.6%
l 11844
20.5%
7180
12.4%
r 4174
 
7.2%
v 3006
 
5.2%
s 2916
 
5.0%
t 2516
 
4.4%
n 1658
 
2.9%
w 1658
 
2.9%
1 1538
 
2.7%
Other values (5) 6500
11.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 57750
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 14760
25.6%
l 11844
20.5%
7180
12.4%
r 4174
 
7.2%
v 3006
 
5.2%
s 2916
 
5.0%
t 2516
 
4.4%
n 1658
 
2.9%
w 1658
 
2.9%
1 1538
 
2.7%
Other values (5) 6500
11.3%
Distinct118
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
2024-05-26T14:52:30.530360image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length16
Median length15
Mean length11.893786
Min length2

Characters and Unicode

Total characters70435
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row293 Results
2nd row293 Results
3rd row293 Results
4th row293 Results
5th row293 Results
ValueCountFrequency (%)
results 5408
47.7%
1,000 226
 
2.0%
2,800 183
 
1.6%
2,000 133
 
1.2%
313 130
 
1.1%
8,900 96
 
0.8%
2,200 95
 
0.8%
1,800 94
 
0.8%
2,700 94
 
0.8%
12,000 93
 
0.8%
Other values (108) 4778
42.2%
2024-05-26T14:52:30.925359image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 10816
15.4%
0 7813
11.1%
l 5408
7.7%
t 5408
7.7%
5408
7.7%
R 5408
7.7%
e 5408
7.7%
u 5408
7.7%
+ 2920
 
4.1%
, 2920
 
4.1%
Other values (9) 13518
19.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 70435
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 10816
15.4%
0 7813
11.1%
l 5408
7.7%
t 5408
7.7%
5408
7.7%
R 5408
7.7%
e 5408
7.7%
u 5408
7.7%
+ 2920
 
4.1%
, 2920
 
4.1%
Other values (9) 13518
19.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 70435
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 10816
15.4%
0 7813
11.1%
l 5408
7.7%
t 5408
7.7%
5408
7.7%
R 5408
7.7%
e 5408
7.7%
u 5408
7.7%
+ 2920
 
4.1%
, 2920
 
4.1%
Other values (9) 13518
19.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 70435
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 10816
15.4%
0 7813
11.1%
l 5408
7.7%
t 5408
7.7%
5408
7.7%
R 5408
7.7%
e 5408
7.7%
u 5408
7.7%
+ 2920
 
4.1%
, 2920
 
4.1%
Other values (9) 13518
19.2%
Distinct333
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
2024-05-26T14:52:31.181448image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length44
Median length3
Mean length4.0119892
Min length2

Characters and Unicode

Total characters23759
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique148 ?
Unique (%)2.5%

Sample

1st row€483.58
2nd row$250
3rd row$50
4th row$120
5th row$100
ValueCountFrequency (%)
10 720
 
11.1%
5 500
 
7.7%
100 412
 
6.4%
30 363
 
5.6%
15 340
 
5.2%
20 316
 
4.9%
50 312
 
4.8%
25 237
 
3.7%
150 189
 
2.9%
40 165
 
2.5%
Other values (306) 2928
45.2%
2024-05-26T14:52:31.583602image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
$ 5388
22.7%
0 4551
19.2%
5 2741
11.5%
1 2518
10.6%
2 1194
 
5.0%
3 905
 
3.8%
4 732
 
3.1%
560
 
2.4%
. 528
 
2.2%
9 453
 
1.9%
Other values (24) 4189
17.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 23759
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
$ 5388
22.7%
0 4551
19.2%
5 2741
11.5%
1 2518
10.6%
2 1194
 
5.0%
3 905
 
3.8%
4 732
 
3.1%
560
 
2.4%
. 528
 
2.2%
9 453
 
1.9%
Other values (24) 4189
17.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 23759
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
$ 5388
22.7%
0 4551
19.2%
5 2741
11.5%
1 2518
10.6%
2 1194
 
5.0%
3 905
 
3.8%
4 732
 
3.1%
560
 
2.4%
. 528
 
2.2%
9 453
 
1.9%
Other values (24) 4189
17.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 23759
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
$ 5388
22.7%
0 4551
19.2%
5 2741
11.5%
1 2518
10.6%
2 1194
 
5.0%
3 905
 
3.8%
4 732
 
3.1%
560
 
2.4%
. 528
 
2.2%
9 453
 
1.9%
Other values (24) 4189
17.6%
Distinct477
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
2024-05-26T14:52:31.877820image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length44
Median length43
Mean length4.3191489
Min length2

Characters and Unicode

Total characters25578
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique232 ?
Unique (%)3.9%

Sample

1st row€677.01
2nd row$450
3rd row$100
4th row$200
5th row$300
ValueCountFrequency (%)
50 341
 
5.3%
10 268
 
4.1%
20 266
 
4.1%
100 234
 
3.6%
30 228
 
3.5%
150 221
 
3.4%
25 218
 
3.4%
15 203
 
3.1%
40 199
 
3.1%
200 178
 
2.7%
Other values (450) 4126
63.7%
2024-05-26T14:52:32.319020image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
$ 5388
21.1%
0 5231
20.5%
5 2824
11.0%
1 2109
 
8.2%
2 1598
 
6.2%
3 977
 
3.8%
4 850
 
3.3%
6 623
 
2.4%
7 621
 
2.4%
9 564
 
2.2%
Other values (24) 4793
18.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25578
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
$ 5388
21.1%
0 5231
20.5%
5 2824
11.0%
1 2109
 
8.2%
2 1598
 
6.2%
3 977
 
3.8%
4 850
 
3.3%
6 623
 
2.4%
7 621
 
2.4%
9 564
 
2.2%
Other values (24) 4793
18.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25578
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
$ 5388
21.1%
0 5231
20.5%
5 2824
11.0%
1 2109
 
8.2%
2 1598
 
6.2%
3 977
 
3.8%
4 850
 
3.3%
6 623
 
2.4%
7 621
 
2.4%
9 564
 
2.2%
Other values (24) 4793
18.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25578
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
$ 5388
21.1%
0 5231
20.5%
5 2824
11.0%
1 2109
 
8.2%
2 1598
 
6.2%
3 977
 
3.8%
4 850
 
3.3%
6 623
 
2.4%
7 621
 
2.4%
9 564
 
2.2%
Other values (24) 4793
18.7%
Distinct579
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
2024-05-26T14:52:32.631342image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length44
Median length43
Mean length4.5633232
Min length2

Characters and Unicode

Total characters27024
Distinct characters34
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique291 ?
Unique (%)4.9%

Sample

1st row€962.32
2nd row$950
3rd row$150
4th row$400
5th row$450
ValueCountFrequency (%)
100 351
 
5.4%
50 227
 
3.5%
150 215
 
3.3%
200 215
 
3.3%
to 160
 
2.5%
30 160
 
2.5%
300 154
 
2.4%
250 147
 
2.3%
20 146
 
2.3%
500 143
 
2.2%
Other values (552) 4564
70.4%
2024-05-26T14:52:33.087991image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 6037
22.3%
$ 5388
19.9%
5 2829
10.5%
1 2144
 
7.9%
2 1556
 
5.8%
3 1109
 
4.1%
4 944
 
3.5%
9 710
 
2.6%
6 643
 
2.4%
7 612
 
2.3%
Other values (24) 5052
18.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27024
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 6037
22.3%
$ 5388
19.9%
5 2829
10.5%
1 2144
 
7.9%
2 1556
 
5.8%
3 1109
 
4.1%
4 944
 
3.5%
9 710
 
2.6%
6 643
 
2.4%
7 612
 
2.3%
Other values (24) 5052
18.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27024
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 6037
22.3%
$ 5388
19.9%
5 2829
10.5%
1 2144
 
7.9%
2 1556
 
5.8%
3 1109
 
4.1%
4 944
 
3.5%
9 710
 
2.6%
6 643
 
2.4%
7 612
 
2.3%
Other values (24) 5052
18.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27024
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 6037
22.3%
$ 5388
19.9%
5 2829
10.5%
1 2144
 
7.9%
2 1556
 
5.8%
3 1109
 
4.1%
4 944
 
3.5%
9 710
 
2.6%
6 643
 
2.4%
7 612
 
2.3%
Other values (24) 5052
18.7%

Basic Delivery
Categorical

Distinct29
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
2 days
1305 
3 days
1109 
1 day
1105 
5 days
442 
7 days
440 
Other values (24)
1521 

Length

Max length15
Median length6
Mean length6.817798
Min length5

Characters and Unicode

Total characters40375
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row7 days
2nd row3 days
3rd row1 day
4th row2 days
5th row7 days

Common Values

ValueCountFrequency (%)
2 days 1305
22.0%
3 days 1109
18.7%
1 day 1105
18.7%
5 days 442
 
7.5%
7 days 440
 
7.4%
4 days 322
 
5.4%
10 days 182
 
3.1%
14 days 152
 
2.6%
2-day delivery 142
 
2.4%
1-day delivery 130
 
2.2%
Other values (19) 593
10.0%

Length

2024-05-26T14:52:33.253577image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
days 4144
35.0%
2 1305
 
11.0%
3 1109
 
9.4%
1 1105
 
9.3%
day 1105
 
9.3%
delivery 673
 
5.7%
5 442
 
3.7%
7 440
 
3.7%
4 322
 
2.7%
10 182
 
1.5%
Other values (22) 1017
 
8.6%

Most occurring characters

ValueCountFrequency (%)
d 6595
16.3%
y 6595
16.3%
a 5922
14.7%
5922
14.7%
s 4144
10.3%
1 1694
 
4.2%
2 1517
 
3.8%
e 1346
 
3.3%
3 1315
 
3.3%
l 673
 
1.7%
Other values (10) 4652
11.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 40375
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 6595
16.3%
y 6595
16.3%
a 5922
14.7%
5922
14.7%
s 4144
10.3%
1 1694
 
4.2%
2 1517
 
3.8%
e 1346
 
3.3%
3 1315
 
3.3%
l 673
 
1.7%
Other values (10) 4652
11.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 40375
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 6595
16.3%
y 6595
16.3%
a 5922
14.7%
5922
14.7%
s 4144
10.3%
1 1694
 
4.2%
2 1517
 
3.8%
e 1346
 
3.3%
3 1315
 
3.3%
l 673
 
1.7%
Other values (10) 4652
11.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 40375
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 6595
16.3%
y 6595
16.3%
a 5922
14.7%
5922
14.7%
s 4144
10.3%
1 1694
 
4.2%
2 1517
 
3.8%
e 1346
 
3.3%
3 1315
 
3.3%
l 673
 
1.7%
Other values (10) 4652
11.5%
Distinct31
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
3 days
992 
2 days
864 
5 days
721 
7 days
628 
4 days
574 
Other values (26)
2143 

Length

Max length15
Median length6
Mean length7.0359676
Min length5

Characters and Unicode

Total characters41667
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.1%

Sample

1st row14 days
2nd row5 days
3rd row3 days
4th row3 days
5th row10 days

Common Values

ValueCountFrequency (%)
3 days 992
16.8%
2 days 864
14.6%
5 days 721
12.2%
7 days 628
10.6%
4 days 574
9.7%
10 days 352
 
5.9%
1 day 323
 
5.5%
14 days 297
 
5.0%
6 days 177
 
3.0%
21 days 145
 
2.4%
Other values (21) 849
14.3%

Length

2024-05-26T14:52:33.385576image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
days 4926
41.6%
3 992
 
8.4%
2 864
 
7.3%
5 721
 
6.1%
delivery 673
 
5.7%
7 628
 
5.3%
4 574
 
4.8%
10 352
 
3.0%
day 323
 
2.7%
1 323
 
2.7%
Other values (24) 1468
 
12.4%

Most occurring characters

ValueCountFrequency (%)
d 6595
15.8%
y 6595
15.8%
5922
14.2%
a 5922
14.2%
s 4926
11.8%
e 1346
 
3.2%
1 1318
 
3.2%
3 1267
 
3.0%
2 1165
 
2.8%
4 961
 
2.3%
Other values (10) 5650
13.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 41667
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 6595
15.8%
y 6595
15.8%
5922
14.2%
a 5922
14.2%
s 4926
11.8%
e 1346
 
3.2%
1 1318
 
3.2%
3 1267
 
3.0%
2 1165
 
2.8%
4 961
 
2.3%
Other values (10) 5650
13.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 41667
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 6595
15.8%
y 6595
15.8%
5922
14.2%
a 5922
14.2%
s 4926
11.8%
e 1346
 
3.2%
1 1318
 
3.2%
3 1267
 
3.0%
2 1165
 
2.8%
4 961
 
2.3%
Other values (10) 5650
13.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 41667
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 6595
15.8%
y 6595
15.8%
5922
14.2%
a 5922
14.2%
s 4926
11.8%
e 1346
 
3.2%
1 1318
 
3.2%
3 1267
 
3.0%
2 1165
 
2.8%
4 961
 
2.3%
Other values (10) 5650
13.6%

Premium Delivery
Categorical

Distinct33
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
7 days
885 
3 days
715 
5 days
686 
10 days
560 
4 days
459 
Other values (28)
2617 

Length

Max length15
Median length6
Mean length7.1702128
Min length5

Characters and Unicode

Total characters42462
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row14 days
2nd row7 days
3rd row5 days
4th row10 days
5th row7 days

Common Values

ValueCountFrequency (%)
7 days 885
14.9%
3 days 715
12.1%
5 days 686
11.6%
10 days 560
9.5%
4 days 459
7.8%
14 days 430
7.3%
2 days 390
 
6.6%
30 days 324
 
5.5%
6 days 224
 
3.8%
1 day 223
 
3.8%
Other values (23) 1026
17.3%

Length

2024-05-26T14:52:33.522618image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
days 5026
42.4%
7 885
 
7.5%
3 715
 
6.0%
5 686
 
5.8%
delivery 673
 
5.7%
10 560
 
4.7%
4 459
 
3.9%
14 430
 
3.6%
2 390
 
3.3%
30 324
 
2.7%
Other values (26) 1696
 
14.3%

Most occurring characters

ValueCountFrequency (%)
d 6595
15.5%
y 6595
15.5%
5922
13.9%
a 5922
13.9%
s 5026
11.8%
1 1617
 
3.8%
e 1346
 
3.2%
3 1181
 
2.8%
0 1020
 
2.4%
4 1018
 
2.4%
Other values (11) 6220
14.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 42462
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
d 6595
15.5%
y 6595
15.5%
5922
13.9%
a 5922
13.9%
s 5026
11.8%
1 1617
 
3.8%
e 1346
 
3.2%
3 1181
 
2.8%
0 1020
 
2.4%
4 1018
 
2.4%
Other values (11) 6220
14.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 42462
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
d 6595
15.5%
y 6595
15.5%
5922
13.9%
a 5922
13.9%
s 5026
11.8%
1 1617
 
3.8%
e 1346
 
3.2%
3 1181
 
2.8%
0 1020
 
2.4%
4 1018
 
2.4%
Other values (11) 6220
14.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 42462
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
d 6595
15.5%
y 6595
15.5%
5922
13.9%
a 5922
13.9%
s 5026
11.8%
1 1617
 
3.8%
e 1346
 
3.2%
3 1181
 
2.8%
0 1020
 
2.4%
4 1018
 
2.4%
Other values (11) 6220
14.6%

Basic Revision
Categorical

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
-1
2340 
1
1060 
Unlimited
791 
2
657 
0
323 
Other values (15)
751 

Length

Max length19
Median length11
Mean length2.9805809
Min length1

Characters and Unicode

Total characters17651
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row1
3rd row0
4th row1
5th row1

Common Values

ValueCountFrequency (%)
-1 2340
39.5%
1 1060
17.9%
Unlimited 791
 
13.4%
2 657
 
11.1%
0 323
 
5.5%
3 322
 
5.4%
5 99
 
1.7%
1 Revision 87
 
1.5%
Unlimited Revisions 71
 
1.2%
2 Revisions 53
 
0.9%
Other values (10) 119
 
2.0%

Length

2024-05-26T14:52:33.675690image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 3487
56.4%
unlimited 862
 
13.9%
2 710
 
11.5%
3 352
 
5.7%
0 323
 
5.2%
revisions 171
 
2.8%
5 111
 
1.8%
revision 87
 
1.4%
4 44
 
0.7%
9 17
 
0.3%
Other values (3) 16
 
0.3%

Most occurring characters

ValueCountFrequency (%)
1 3487
19.8%
- 2340
13.3%
i 2240
12.7%
n 1120
 
6.3%
e 1120
 
6.3%
U 862
 
4.9%
l 862
 
4.9%
m 862
 
4.9%
t 862
 
4.9%
d 862
 
4.9%
Other values (14) 3034
17.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 17651
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 3487
19.8%
- 2340
13.3%
i 2240
12.7%
n 1120
 
6.3%
e 1120
 
6.3%
U 862
 
4.9%
l 862
 
4.9%
m 862
 
4.9%
t 862
 
4.9%
d 862
 
4.9%
Other values (14) 3034
17.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 17651
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 3487
19.8%
- 2340
13.3%
i 2240
12.7%
n 1120
 
6.3%
e 1120
 
6.3%
U 862
 
4.9%
l 862
 
4.9%
m 862
 
4.9%
t 862
 
4.9%
d 862
 
4.9%
Other values (14) 3034
17.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 17651
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 3487
19.8%
- 2340
13.3%
i 2240
12.7%
n 1120
 
6.3%
e 1120
 
6.3%
U 862
 
4.9%
l 862
 
4.9%
m 862
 
4.9%
t 862
 
4.9%
d 862
 
4.9%
Other values (14) 3034
17.2%
Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
-1
2340 
Unlimited
893 
2
834 
1
581 
3
454 
Other values (15)
820 

Length

Max length19
Median length11
Mean length3.1183722
Min length1

Characters and Unicode

Total characters18467
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row2
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
-1 2340
39.5%
Unlimited 893
 
15.1%
2 834
 
14.1%
1 581
 
9.8%
3 454
 
7.7%
5 206
 
3.5%
0 138
 
2.3%
4 114
 
1.9%
1 Revision 87
 
1.5%
Unlimited Revisions 71
 
1.2%
Other values (10) 204
 
3.4%

Length

2024-05-26T14:52:33.828720image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 3008
48.7%
unlimited 964
 
15.6%
2 887
 
14.4%
3 484
 
7.8%
5 218
 
3.5%
revisions 171
 
2.8%
0 138
 
2.2%
4 117
 
1.9%
revision 87
 
1.4%
9 37
 
0.6%
Other values (3) 69
 
1.1%

Most occurring characters

ValueCountFrequency (%)
1 3008
16.3%
i 2444
13.2%
- 2340
12.7%
e 1222
 
6.6%
n 1222
 
6.6%
l 964
 
5.2%
m 964
 
5.2%
t 964
 
5.2%
d 964
 
5.2%
U 964
 
5.2%
Other values (14) 3411
18.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 18467
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 3008
16.3%
i 2444
13.2%
- 2340
12.7%
e 1222
 
6.6%
n 1222
 
6.6%
l 964
 
5.2%
m 964
 
5.2%
t 964
 
5.2%
d 964
 
5.2%
U 964
 
5.2%
Other values (14) 3411
18.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 18467
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 3008
16.3%
i 2444
13.2%
- 2340
12.7%
e 1222
 
6.6%
n 1222
 
6.6%
l 964
 
5.2%
m 964
 
5.2%
t 964
 
5.2%
d 964
 
5.2%
U 964
 
5.2%
Other values (14) 3411
18.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 18467
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 3008
16.3%
i 2444
13.2%
- 2340
12.7%
e 1222
 
6.6%
n 1222
 
6.6%
l 964
 
5.2%
m 964
 
5.2%
t 964
 
5.2%
d 964
 
5.2%
U 964
 
5.2%
Other values (14) 3411
18.5%

Premium Revision
Categorical

Distinct20
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size92.5 KiB
-1
2340 
Unlimited
1177 
2
578 
3
553 
1
369 
Other values (15)
905 

Length

Max length19
Median length11
Mean length3.5020263
Min length1

Characters and Unicode

Total characters20739
Distinct characters24
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st row2
2nd row5
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
-1 2340
39.5%
Unlimited 1177
19.9%
2 578
 
9.8%
3 553
 
9.3%
1 369
 
6.2%
5 242
 
4.1%
4 133
 
2.2%
0 104
 
1.8%
1 Revision 87
 
1.5%
Unlimited Revisions 71
 
1.2%
Other values (10) 268
 
4.5%

Length

2024-05-26T14:52:33.980720image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 2796
45.2%
unlimited 1248
20.2%
2 631
 
10.2%
3 583
 
9.4%
5 254
 
4.1%
revisions 171
 
2.8%
4 136
 
2.2%
0 104
 
1.7%
revision 87
 
1.4%
9 66
 
1.1%
Other values (3) 104
 
1.7%

Most occurring characters

ValueCountFrequency (%)
i 3012
14.5%
1 2796
13.5%
- 2340
11.3%
e 1506
7.3%
n 1506
7.3%
l 1248
 
6.0%
m 1248
 
6.0%
t 1248
 
6.0%
d 1248
 
6.0%
U 1248
 
6.0%
Other values (14) 3339
16.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20739
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 3012
14.5%
1 2796
13.5%
- 2340
11.3%
e 1506
7.3%
n 1506
7.3%
l 1248
 
6.0%
m 1248
 
6.0%
t 1248
 
6.0%
d 1248
 
6.0%
U 1248
 
6.0%
Other values (14) 3339
16.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20739
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 3012
14.5%
1 2796
13.5%
- 2340
11.3%
e 1506
7.3%
n 1506
7.3%
l 1248
 
6.0%
m 1248
 
6.0%
t 1248
 
6.0%
d 1248
 
6.0%
U 1248
 
6.0%
Other values (14) 3339
16.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20739
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 3012
14.5%
1 2796
13.5%
- 2340
11.3%
e 1506
7.3%
n 1506
7.3%
l 1248
 
6.0%
m 1248
 
6.0%
t 1248
 
6.0%
d 1248
 
6.0%
U 1248
 
6.0%
Other values (14) 3339
16.1%

Rating
Real number (ℝ)

MISSING 

Distinct20
Distinct (%)0.3%
Missing104
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean4.9345308
Minimum1
Maximum5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size92.5 KiB
2024-05-26T14:52:34.116682image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.8
Q14.9
median5
Q35
95-th percentile5
Maximum5
Range4
Interquartile range (IQR)0.1

Descriptive statistics

Standard deviation0.19144177
Coefficient of variation (CV)0.038796348
Kurtosis242.14932
Mean4.9345308
Median Absolute Deviation (MAD)0
Skewness-13.293237
Sum28709.1
Variance0.036649952
MonotonicityNot monotonic
2024-05-26T14:52:34.265661image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
5 3595
60.7%
4.9 1599
27.0%
4.8 390
 
6.6%
4.7 121
 
2.0%
4.6 32
 
0.5%
4.5 21
 
0.4%
4.3 16
 
0.3%
4 11
 
0.2%
1 7
 
0.1%
4.4 6
 
0.1%
Other values (10) 20
 
0.3%
(Missing) 104
 
1.8%
ValueCountFrequency (%)
1 7
0.1%
1.7 1
 
< 0.1%
2.8 1
 
< 0.1%
3 4
 
0.1%
3.2 2
 
< 0.1%
3.3 1
 
< 0.1%
3.5 1
 
< 0.1%
3.7 1
 
< 0.1%
3.8 1
 
< 0.1%
4 11
0.2%
ValueCountFrequency (%)
5 3595
60.7%
4.9 1599
27.0%
4.8 390
 
6.6%
4.7 121
 
2.0%
4.6 32
 
0.5%
4.5 21
 
0.4%
4.4 6
 
0.1%
4.3 16
 
0.3%
4.2 4
 
0.1%
4.1 4
 
0.1%

Rating Count
Text

MISSING 

Distinct1058
Distinct (%)18.2%
Missing104
Missing (%)1.8%
Memory size92.5 KiB
2024-05-26T14:52:34.567994image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length6
Median length5
Mean length2.5713304
Min length1

Characters and Unicode

Total characters14960
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique514 ?
Unique (%)8.8%

Sample

1st row3.0
2nd row5.0
3rd row12.0
4th row13.0
5th row8.0
ValueCountFrequency (%)
3 104
 
1.8%
2 102
 
1.8%
1.0 101
 
1.7%
1 93
 
1.6%
4 85
 
1.5%
5 80
 
1.4%
7 76
 
1.3%
11 72
 
1.2%
12 71
 
1.2%
3.0 70
 
1.2%
Other values (1048) 4964
85.3%
2024-05-26T14:52:35.021094image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 2633
17.6%
2 1822
12.2%
0 1794
12.0%
3 1509
10.1%
4 1218
8.1%
5 1154
7.7%
. 999
 
6.7%
6 963
 
6.4%
7 939
 
6.3%
8 854
 
5.7%
Other values (2) 1075
7.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14960
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 2633
17.6%
2 1822
12.2%
0 1794
12.0%
3 1509
10.1%
4 1218
8.1%
5 1154
7.7%
. 999
 
6.7%
6 963
 
6.4%
7 939
 
6.3%
8 854
 
5.7%
Other values (2) 1075
7.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14960
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 2633
17.6%
2 1822
12.2%
0 1794
12.0%
3 1509
10.1%
4 1218
8.1%
5 1154
7.7%
. 999
 
6.7%
6 963
 
6.4%
7 939
 
6.3%
8 854
 
5.7%
Other values (2) 1075
7.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14960
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 2633
17.6%
2 1822
12.2%
0 1794
12.0%
3 1509
10.1%
4 1218
8.1%
5 1154
7.7%
. 999
 
6.7%
6 963
 
6.4%
7 939
 
6.3%
8 854
 
5.7%
Other values (2) 1075
7.2%
Distinct113
Distinct (%)1.9%
Missing1
Missing (%)< 0.1%
Memory size92.5 KiB
2024-05-26T14:52:35.254590image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length22
Median length19
Mean length8.7098463
Min length4

Characters and Unicode

Total characters51571
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)0.3%

Sample

1st rowPakistan
2nd rowPakistan
3rd rowPakistan
4th rowUnited States
5th rowUnited Kingdom
ValueCountFrequency (%)
pakistan 1441
19.8%
united 1123
15.4%
states 744
 
10.2%
bangladesh 487
 
6.7%
india 436
 
6.0%
kingdom 352
 
4.8%
nigeria 144
 
2.0%
germany 123
 
1.7%
sri 123
 
1.7%
lanka 123
 
1.7%
Other values (118) 2200
30.2%
2024-05-26T14:52:35.657319image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 7856
15.2%
n 5424
 
10.5%
i 5044
 
9.8%
t 4551
 
8.8%
e 3933
 
7.6%
s 3051
 
5.9%
d 2847
 
5.5%
k 1740
 
3.4%
P 1575
 
3.1%
1375
 
2.7%
Other values (42) 14175
27.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 51571
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 7856
15.2%
n 5424
 
10.5%
i 5044
 
9.8%
t 4551
 
8.8%
e 3933
 
7.6%
s 3051
 
5.9%
d 2847
 
5.5%
k 1740
 
3.4%
P 1575
 
3.1%
1375
 
2.7%
Other values (42) 14175
27.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 51571
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 7856
15.2%
n 5424
 
10.5%
i 5044
 
9.8%
t 4551
 
8.8%
e 3933
 
7.6%
s 3051
 
5.9%
d 2847
 
5.5%
k 1740
 
3.4%
P 1575
 
3.1%
1375
 
2.7%
Other values (42) 14175
27.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 51571
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 7856
15.2%
n 5424
 
10.5%
i 5044
 
9.8%
t 4551
 
8.8%
e 3933
 
7.6%
s 3051
 
5.9%
d 2847
 
5.5%
k 1740
 
3.4%
P 1575
 
3.1%
1375
 
2.7%
Other values (42) 14175
27.5%

Member Since
Date

MISSING 

Distinct149
Distinct (%)3.4%
Missing1571
Missing (%)26.5%
Memory size92.5 KiB
Minimum2011-03-01 00:00:00
Maximum2024-05-01 00:00:00
2024-05-26T14:52:35.987394image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
2024-05-26T14:52:36.161397image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Avg Response Time
Categorical

IMBALANCE  MISSING 

Distinct34
Distinct (%)0.8%
Missing1685
Missing (%)28.5%
Memory size92.5 KiB
1 hour
2544 
2 hours
505 
3 hours
300 
4 hours
 
221
5 hours
 
131
Other values (29)
536 

Length

Max length8
Median length6
Mean length6.3995752
Min length5

Characters and Unicode

Total characters27115
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.1%

Sample

1st row1 hour
2nd row1 hour
3rd row2 hours
4th row1 hour
5th row2 hours

Common Values

ValueCountFrequency (%)
1 hour 2544
43.0%
2 hours 505
 
8.5%
3 hours 300
 
5.1%
4 hours 221
 
3.7%
5 hours 131
 
2.2%
6 hours 90
 
1.5%
7 hours 58
 
1.0%
8 hours 55
 
0.9%
9 hours 46
 
0.8%
1 day 45
 
0.8%
Other values (24) 242
 
4.1%
(Missing) 1685
28.5%

Length

2024-05-26T14:52:36.321402image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
1 2589
30.6%
hour 2544
30.0%
hours 1568
18.5%
2 542
 
6.4%
3 319
 
3.8%
4 229
 
2.7%
5 132
 
1.6%
6 96
 
1.1%
days 80
 
0.9%
7 59
 
0.7%
Other values (18) 316
 
3.7%

Most occurring characters

ValueCountFrequency (%)
4237
15.6%
h 4112
15.2%
o 4112
15.2%
u 4112
15.2%
r 4112
15.2%
1 2767
10.2%
s 1648
 
6.1%
2 595
 
2.2%
3 337
 
1.2%
4 237
 
0.9%
Other values (9) 846
 
3.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 27115
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
4237
15.6%
h 4112
15.2%
o 4112
15.2%
u 4112
15.2%
r 4112
15.2%
1 2767
10.2%
s 1648
 
6.1%
2 595
 
2.2%
3 337
 
1.2%
4 237
 
0.9%
Other values (9) 846
 
3.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 27115
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
4237
15.6%
h 4112
15.2%
o 4112
15.2%
u 4112
15.2%
r 4112
15.2%
1 2767
10.2%
s 1648
 
6.1%
2 595
 
2.2%
3 337
 
1.2%
4 237
 
0.9%
Other values (9) 846
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 27115
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
4237
15.6%
h 4112
15.2%
o 4112
15.2%
u 4112
15.2%
r 4112
15.2%
1 2767
10.2%
s 1648
 
6.1%
2 595
 
2.2%
3 337
 
1.2%
4 237
 
0.9%
Other values (9) 846
 
3.1%

Last Delivery
Text

MISSING 

Distinct91
Distinct (%)2.1%
Missing1574
Missing (%)26.6%
Memory size92.5 KiB
2024-05-26T14:52:36.476396image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length16
Median length14
Mean length8.3861546
Min length5

Characters and Unicode

Total characters36463
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)0.3%

Sample

1st row5 days
2nd rowabout 6 hours
3rd row2 months
4th row1 week
5th rowabout 18 hours
ValueCountFrequency (%)
1 1360
13.6%
about 1271
12.8%
hours 1127
11.3%
days 1031
10.3%
2 802
 
8.0%
day 605
 
6.1%
3 521
 
5.2%
week 450
 
4.5%
weeks 375
 
3.8%
months 361
 
3.6%
Other values (52) 2064
20.7%
2024-05-26T14:52:36.791574image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5619
15.4%
o 3027
 
8.3%
s 2988
 
8.2%
a 2950
 
8.1%
u 2544
 
7.0%
1 1936
 
5.3%
t 1932
 
5.3%
e 1781
 
4.9%
h 1754
 
4.8%
y 1679
 
4.6%
Other values (18) 10253
28.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36463
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
5619
15.4%
o 3027
 
8.3%
s 2988
 
8.2%
a 2950
 
8.1%
u 2544
 
7.0%
1 1936
 
5.3%
t 1932
 
5.3%
e 1781
 
4.9%
h 1754
 
4.8%
y 1679
 
4.6%
Other values (18) 10253
28.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36463
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
5619
15.4%
o 3027
 
8.3%
s 2988
 
8.2%
a 2950
 
8.1%
u 2544
 
7.0%
1 1936
 
5.3%
t 1932
 
5.3%
e 1781
 
4.9%
h 1754
 
4.8%
y 1679
 
4.6%
Other values (18) 10253
28.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36463
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
5619
15.4%
o 3027
 
8.3%
s 2988
 
8.2%
a 2950
 
8.1%
u 2544
 
7.0%
1 1936
 
5.3%
t 1932
 
5.3%
e 1781
 
4.9%
h 1754
 
4.8%
y 1679
 
4.6%
Other values (18) 10253
28.1%
Distinct1018
Distinct (%)17.3%
Missing25
Missing (%)0.4%
Memory size92.5 KiB
2024-05-26T14:52:36.978580image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length50
Median length45
Mean length18.863659
Min length4

Characters and Unicode

Total characters111239
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique600 ?
Unique (%)10.2%

Sample

1st rowI speak Urdu, English
2nd rowI speak English, Urdu
3rd rowI speak Urdu, English
4th rowI speak English
5th rowI speak English, Polish
ValueCountFrequency (%)
english 5867
36.9%
speak 1515
 
9.5%
i 1515
 
9.5%
spanish 1178
 
7.4%
french 856
 
5.4%
urdu 822
 
5.2%
german 770
 
4.8%
hindi 557
 
3.5%
italian 274
 
1.7%
bengali 270
 
1.7%
Other values (99) 2275
 
14.3%
2024-05-26T14:52:37.353578image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 11342
 
10.2%
i 10477
 
9.4%
10002
 
9.0%
s 9696
 
8.7%
h 8473
 
7.6%
, 6951
 
6.2%
l 6764
 
6.1%
g 6448
 
5.8%
a 6385
 
5.7%
E 5876
 
5.3%
Other values (42) 28825
25.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 111239
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 11342
 
10.2%
i 10477
 
9.4%
10002
 
9.0%
s 9696
 
8.7%
h 8473
 
7.6%
, 6951
 
6.2%
l 6764
 
6.1%
g 6448
 
5.8%
a 6385
 
5.7%
E 5876
 
5.3%
Other values (42) 28825
25.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 111239
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 11342
 
10.2%
i 10477
 
9.4%
10002
 
9.0%
s 9696
 
8.7%
h 8473
 
7.6%
, 6951
 
6.2%
l 6764
 
6.1%
g 6448
 
5.8%
a 6385
 
5.7%
E 5876
 
5.3%
Other values (42) 28825
25.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 111239
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 11342
 
10.2%
i 10477
 
9.4%
10002
 
9.0%
s 9696
 
8.7%
h 8473
 
7.6%
, 6951
 
6.2%
l 6764
 
6.1%
g 6448
 
5.8%
a 6385
 
5.7%
E 5876
 
5.3%
Other values (42) 28825
25.9%

Order in Queue
Text

MISSING 

Distinct51
Distinct (%)2.4%
Missing3761
Missing (%)63.5%
Memory size92.5 KiB
2024-05-26T14:52:37.504702image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Length

Max length19
Median length17
Mean length16.704304
Min length16

Characters and Unicode

Total characters36098
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique21 ?
Unique (%)1.0%

Sample

1st row1 order in queue
2nd row1 order in queue
3rd row5 orders in queue
4th row1 order in queue
5th row5 orders in queue
ValueCountFrequency (%)
in 2161
25.0%
queue 2161
25.0%
orders 1339
15.5%
1 822
 
9.5%
order 822
 
9.5%
2 443
 
5.1%
3 249
 
2.9%
4 159
 
1.8%
5 109
 
1.3%
6 85
 
1.0%
Other values (45) 294
 
3.4%
2024-05-26T14:52:37.807589image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 6483
18.0%
6483
18.0%
r 4322
12.0%
u 4322
12.0%
o 2161
 
6.0%
d 2161
 
6.0%
i 2161
 
6.0%
n 2161
 
6.0%
q 2161
 
6.0%
s 1339
 
3.7%
Other values (10) 2344
 
6.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 36098
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 6483
18.0%
6483
18.0%
r 4322
12.0%
u 4322
12.0%
o 2161
 
6.0%
d 2161
 
6.0%
i 2161
 
6.0%
n 2161
 
6.0%
q 2161
 
6.0%
s 1339
 
3.7%
Other values (10) 2344
 
6.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 36098
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 6483
18.0%
6483
18.0%
r 4322
12.0%
u 4322
12.0%
o 2161
 
6.0%
d 2161
 
6.0%
i 2161
 
6.0%
n 2161
 
6.0%
q 2161
 
6.0%
s 1339
 
3.7%
Other values (10) 2344
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 36098
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 6483
18.0%
6483
18.0%
r 4322
12.0%
u 4322
12.0%
o 2161
 
6.0%
d 2161
 
6.0%
i 2161
 
6.0%
n 2161
 
6.0%
q 2161
 
6.0%
s 1339
 
3.7%
Other values (10) 2344
 
6.5%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size52.0 KiB
False
5249 
True
673 
ValueCountFrequency (%)
False 5249
88.6%
True 673
 
11.4%
2024-05-26T14:52:37.935136image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Interactions

2024-05-26T14:52:28.509078image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/

Missing values

2024-05-26T14:52:28.752131image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-26T14:52:29.129715image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-05-26T14:52:29.402754image/svg+xmlMatplotlib v3.7.5, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

CategoryFieldSeller LevelSeller In Same LevelBasic PriceStandard PricePremium PriceBasic DeliveryStandard DeliveryPremium DeliveryBasic RevisionStandard RevisionPremium RevisionRatingRating CountCountryMember SinceAvg Response TimeLast DeliveryLanguageOrder in Queueis_single_plan
0Datadata-engineeringlevel 1293 Results€483.58€677.01€962.327 days14 days14 days2225.03.0PakistanNaNNaNNaNI speak Urdu, EnglishNaNFalse
1Datadata-engineeringlevel 1293 Results$250$450$9503 days5 days7 days1255.05.0PakistanNaNNaNNaNI speak English, UrduNaNFalse
2Datadata-engineeringlevel 1293 Results$50$100$1501 day3 days5 days0125.012.0PakistanNaNNaNNaNI speak Urdu, EnglishNaNFalse
3Datadata-engineeringlevel 1293 Results$120$200$4002 days3 days10 days1225.013.0United StatesNaNNaNNaNI speak EnglishNaNFalse
4Datadata-engineeringlevel 1293 Results$100$300$4507 days10 days7 days1124.68.0United KingdomNaNNaNNaNI speak English, PolishNaNFalse
5Datadata-engineeringlevel 1293 Results$30$50$951 day2 days3 days1124.922.0PakistanNaNNaNNaNI speak Urdu, English, FrenchNaNFalse
6Datadata-engineeringlevel 1293 Results$80$160$3003 days7 days14 days3335.019.0BangladeshNaNNaNNaNI speak Bengali, EnglishNaNFalse
7Datadata-engineeringlevel 1293 Results$100$2,000$10,0001 day2 days3 days2375.010.0PakistanNaNNaNNaNI speak EnglishNaNFalse
8Datadata-engineeringlevel 1293 Results$200$300$4007 days14 days21 days1235.02.0United StatesNaNNaNNaNI speak English, BulgarianNaNFalse
9Datadata-engineeringlevel 1293 Results$100$100$1005-day delivery5-day delivery5-day delivery1 Revision1 Revision1 Revision5.05.0PakistanNaNNaNNaNI speak Urdu, EnglishNaNTrue
CategoryFieldSeller LevelSeller In Same LevelBasic PriceStandard PricePremium PriceBasic DeliveryStandard DeliveryPremium DeliveryBasic RevisionStandard RevisionPremium RevisionRatingRating CountCountryMember SinceAvg Response TimeLast DeliveryLanguageOrder in Queueis_single_plan
6245Businesssoftware-managementtop rated seller55 Results$150$1,500$3,0001 day3 days7 days-1-1-14.820CanadaDec 20201 hour3 daysEnglish, FrenchNaNFalse
6246Businesssoftware-managementtop rated seller55 Results$50$350$6502 days4 days6 days-1-1-15.09PakistanOct 20181 hourabout 18 hoursEnglish, French, German, SpanishNaNFalse
6247Businesssoftware-managementtop rated seller55 Results$70$130$18010 days10 days10 days-1-1-15.024South AfricaAug 20202 hours2 daysEnglishNaNFalse
6248Businesssoftware-managementtop rated seller55 Results$115$155$18510 days10 days10 days-1-1-15.015South AfricaAug 20202 hours2 daysEnglishNaNFalse
6249Businesssoftware-managementtop rated seller55 Results$500$1,250$3,25010 days10 days14 days-1-1-15.021GermanyJul 20203 hours4 daysEnglishNaNFalse
6254Businesssoftware-managementtop rated seller55 Results$15$60$9010 days10 days10 days-1-1-15.04MexicoApr 20158 hoursabout 16 hoursEnglish, SpanishNaNFalse
6255Businesssoftware-managementtop rated seller55 Results$250$250$25010-day delivery10-day delivery10-day delivery-1-1-15.04PakistanSep 20181 hour6 daysUrdu, EnglishNaNTrue
6256Businesssoftware-managementtop rated seller55 Results$115$155$18510 days10 days10 days-1-1-15.0128South AfricaAug 20202 hours2 daysEnglishNaNFalse
6260Businesssoftware-managementtop rated seller55 Results$50$50$5021-day delivery21-day delivery21-day delivery-1-1-15.036BangladeshMar 20151 hour1 weekEnglishNaNTrue
6261Businesssoftware-managementtop rated seller55 Results$150$1,200$2,2505 days14 days30 days-1-1-15.0175CanadaDec 20201 hour3 daysEnglish, French3 orders in queueFalse